code: def test_resultset_correctness_with_no_parallelization():
      query = {
          "ukbench00120.jpg": "2b69707551f1b87a",
          "ukbench09268.jpg": "ac9c72f8e1c2c448",
      }
      db = {
          "ukbench00120_fake.jpg": "2b69707551f1b87d",
          "ukbench00120_resize.jpg": "2b69707551f1b87a",
          "ukbench09268_2.jpg": "ac9c72f8e1c2c448",
      }
      hasheval_obj = HashEval(
          db,
          query,
          HAMMING_DISTANCE_FUNCTION,
          threshold=3,
          num_dist_workers=0,
      )
      results = hasheval_obj.retrieve_results(scores=True)
      distances = [i[1] for v in results.values() for i in v]
      assert max(distances) == 3
  
file_path: imagededup/tests/test_retrieval.py
imports: import sys
  import pytest
  import numpy
  from sklearn.metrics.pairwise import cosine_similarity
  from imagededup.handlers.search.retrieval import HashEval, cosine_similarity_chunk, get_cosine_similarity
  from imagededup.methods.hashing import Hashing
label_desc: Use image node_id 7 for calling a global function with example usage: test_resultset_correctness_with_no_parallelization() without return types